Dynamic Obstacle Avoidance for Robotic Arms Using Deep Reinforcement Learning with Adaptive Reward Mechanisms

Dynamic Obstacle Avoidance for Robotic Arms Using Deep Reinforcement Learning with Adaptive Reward Mechanisms

To address the challenges of robotic arm path-planning in dynamic environments, this study proposes a reinforcement learning-based dynamic obstacle avoidance method. The study concerns a robot with six rotational degrees of freedom when moving outside of singular configurations, enabling more flexib...

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Bibliographic Details
Main Authors: Sen Yan, Yanping Zhu, Wenlong Chen, Jianqiang Zhang, Chenyang Zhu, Qi Chen
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Applied Sciences
Subjects:
obstacle avoidance
deep reinforcement learning
reward function
robotic arm
Online Access:https://www.mdpi.com/2076-3417/15/8/4496
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